data = read_csv("data.csv") %>%
filter(!`Case Number` %in% readxl::read_xlsx("C:\\Users\\jagvan\\OneDrive - South Australia Government\\Code\\exclusions_2021.xlsx")$`Case Number`) %>%
mutate(`Age Group` = factor(`Age Group`, levels =
c("< 28 days", "1 to 11 months", "1 to 4 years", "5 to 9 years", "10 to 14 years", "15 to 17 years"))) %>%
left_join(read_csv("C:\\Users\\jagvan\\OneDrive - South Australia Government\\REDCap\\ICD-10\\icd-10-chapters.csv")[c("Chapter", "Name")], by = "Chapter")
disability = data %>% filter(`Disability Register` == "Yes") %>%
mutate("Infant with disability" = ifelse(`Age (years)` < 1, "Yes", "No"))
disability_long = pivot_longer(disability,
cols = c(Autism:`Other disability`,`Infant with disability`),
names_to = "Disability_category",
values_to = "Yes_No") %>%
filter(Yes_No == "Yes")
yearly = disability_long %>%
mutate(Disability_category = as.factor(Disability_category),
Disability_category = reorder(Disability_category, Disability_category, FUN=length)) %>%
group_by(`Year of Death`, Disability_category) %>%
tally()
yearly_percentage = data %>%
group_by(`Year of Death`, `Disability Register`) %>%
tally() %>%
pivot_wider(id_cols = `Year of Death`, names_from = `Disability Register`, values_from = n) %>%
mutate(Total = Yes + No,
Prop_disability = Yes/No)
chapter_age = disability %>%
mutate(Chapter = as.factor(Chapter)) %>%
group_by(`Age Group`, Chapter, Name) %>%
tally()
(figure2 <- plot_ly(chapter_age,
type = "bar",
x = ~`Age Group`,
y = ~n,
color = ~fct_rev(Chapter),
hovertemplate = paste0("Chapter ", chapter_age$Chapter, ": ", chapter_age$Name, "\n",
"Deaths: ", chapter_age$n, "<extra></extra>")) %>%
layout(barmode = "stack",
font = list(size = 14),
xaxis = list(title = "Age group"),
yaxis = list(title = "Deaths"),
legend = list(title = list(text="ICD-10\nChapter",
font=list(size=12)),
font=list(size = 12)))
)
saveWidget(partial_bundle(figure2), "figure2.html", selfcontained = T)
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